Pulse compression allows a radar to obtain the range resolution of a short pulse without the need for very high peak transmit power. This is accomplished by transmitting a long pulse that is phase or frequency modulated. The modulated pulse, or waveform, is reflected back to the radar by scatterers that lie in the transmission path. This process can be viewed as the convolution of the transmitted waveform with an impulse response that is representative of the range profile illuminated by the radar. The purpose of pulse compression is then to estimate the range profile impulse response based upon the known transmitted waveform and the received radar return signal.
The traditional method of pulse compression is known as matched filtering which has been shown to maximize the received signal-to-noise ratio (SNR) for a solitary point scatterer. In the discreet domain, matched filtering can be expressed as{circumflex over (x)}NIF(Λ)=sHy(Λ)  (1)where {circumflex over (x)}NIF(Λ), for Λ=0, . . . , L−1, is the estimate of the Λth delayed sample (range cell index). s=[s1 s2 . . . sN]T is the length−N sampled version of the transmitted waveform. y(Λ)=[y(Λ) y(Λ+1) . . . y(Λ+N−1)]T is a vector of N contiguous samples of the received radar return signal, and (•)H is the complex-conjugate transpose (or Hermitian) operation. Matched filtering, however, is plagued by range sidelobes that can cause the presence of large targets to mask nearby small targets thus limiting radar sensitivity.
Numerous approaches have been developed to reduce the range sidelobes resulting from matched filtering. These approaches include optimal mismatched filtering and Least-Squares estimation, as well as numerous other variations of each. Adaptivity in pulse compression was first introduced by W. F. Gabriel. “Superresolution techniques in the range domain.” IEEE International Radar Conf., pp. 263-267. May 1990 and “Superresolution techniques and ISAR imaging,” Naval Research Laboratory Memorandum Report, No. 6714. Sep. 21, 1990. in which numerous (>200) pulses were employed to estimate a sample covariance matrix with which to cancel the range sidelobes.
In another approach described in U.S. Pat. No. 6,940,450. Blunt et al., issued Sep. 6, 2005, and incorporated herein by reference, adaptive pulse compression (APC) by way of Reiterative Minimum Mean-Square Error (RMMSE) estimation has been shown to be an effective ay to mitigate range sidelobes on a single pulse basis. However, while still superior to the matched filter, APC can suffer degradation due to Doppler mismatch for targets with high radial velocity with respect to the radar.
There is, therefore, a need for an adaptive pulse compression system with improved robustness, accuracy, and resolution.